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Roastify Fetch Design

roastify_fetch_design

Fetch one of your stored designs in full, with its images re-inlined.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
refNoOptional git ref (a commit sha or version tag) to fetch a specific version — from roastify_list_design_versions. Omit for the latest.
npubNoRequired. Your Nostr public key (npub1...) for credit billing.
design_idYesThe id from roastify_stash_design or roastify_list_designs.
dpop_tokenNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

A3.8/5.0
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

There are no annotations, so the description carries the disclosure burden. It does reveal an important behavior ('images re-inlined') and implies a read-only fetch, but it does not mention authentication requirements, credit billing, or any side effects, which is relevant given the npub/credit-billing context.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, front-loaded sentence with no filler. It names the verb, the resource, and the key behavioral detail in a compact structure that is easy for an agent to parse quickly.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

An output schema exists, so the description does not need to explain return values, and the parameter schema covers most inputs. The main missing context is explicit usage guidance and side-effect disclosure, but for a straightforward fetch operation the description is otherwise adequate.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema already provides descriptions for design_id, ref, and npub, covering roughly 75% of parameters. The tool description does not add parameter-level meaning and does not clarify the undocumented dpop_token, but it also does not need to duplicate what the schema already conveys.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses a specific verb ('Fetch') with a clear resource ('one of your stored designs') and adds the meaningful qualifier 'in full, with its images re-inlined.' This distinguishes it from listing tools like roastify_list_designs and from partial-retrieval tools like roastify_get_design_text, so an agent can identify the correct operation without opening the schema.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No explicit alternatives or when-not-to-use conditions are given, but the wording implies this is the tool for retrieving a complete stored design rather than a list or text-only view. The guidance is mostly implicit and could be stronger by naming relevant siblings such as roastify_list_designs or roastify_list_design_versions.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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TDQS

B3.4/5.0
Disambiguation4/5

Most tools target clearly distinct resources—patron balances vs. operator Authority balances, design text vs. full design fetches, operator vs. patron credentials—and the verbose descriptions carefully separate request/receive flows. A few pairs could still be confused at a glance, such as service_status/session_status, forget_coupon/delete_coupon, and get_design_text/fetch_design.

Naming Consistency4/5

All tools share the roastify_ snake_case prefix and mostly follow a verb_noun pattern like list_, get_, update_, delete_, and create. However, several noun-only names (service_status, session_status, account_statement, oracle_about) and the inconsistent forget_ vs. delete_ distinction for credential/coupon removal keep it from being fully consistent.

Tool Count1/5

69 tools is an extreme count for a single MCP surface and far exceeds the 25+ threshold. Even though the tools span many subdomains—design, payments, coupons, credentials, pricing, notarization, oracle—the sheer number will be heavy on agent context and selection accuracy.

Completeness3/5

Core workflows are largely covered: design storage/editing, coupon lifecycle, credential vaults, credit purchasing, pricing models, notarization, and the oracle all have reasonable read/write surfaces. However, session_status explicitly tells not_registered operators to call register_operator, which does not exist in the tool set, and design editing lacks any delete-element operation, leaving notable dead ends.